couldn't have said it any better

it came from the data (UN Comtrade) that notably doesn't include sanctioned oil flows (Iran, etc). On top of that, China's reserve levels are a state secret, yet, the model's framework is BYOD (Bring Your Own Data) which gives the depletion timeline for free. Also, the model is more of a sensible baseline than a prediction

Thanks! Two answers (repeated in other comments): UN Comtrade data doesn't include sanctioned oil (Iran), and nobody (except their government) knows China's actual stockpile. The model is more of a sensible baseline/stress testing tool than a prediction, the cool part is that anyone can BTON (bring their own numbers) and rerun their scenarios

Thanks, added to list of possible UX improvements

Yes, and the network setting is flexible enough to allow smaller supply chains where nodes don't have price setting power

the models, proofs and writing are mine (with some AI assistance for proofreading/formatting). AI was mostly used in the visualization and the rerunning of multiple scenarios of the numerical examples

This pipeline predates the data but its oil is routed to Bab-el-Mandeb which is in the network. That being said, the numbers are more of a sensible baseline as the actual flows for many countries are unknown/sanctioned.

This is an interesting insight, as usable reserves < reported reserves the clocks in the model are optimistic

Fair catch, the data predates the reroute. Although this pipeline is routed to Bab-el-Mandeb which is in the network

That's actually the intended behavior: while reserves are silently being spend is when the crisis is brewing. Although the main point is that nobody knows China's reserves, but this allows to calibrates scenarios based on what you believe is plausible